I am doing a project on indoor localisation using fingerprinting. Is it possible to build a system in LabView which can scan the entire spectrum and provide me the RSSI measurements of different types of signals?(say FM, GSM, DVB-T and so on.) In case it has to be done separately, can someone please point me to some resources that would help me to find the RSSIs of say, FM signals? I am new to SDRs and would really appreciate some help. I have used this paper as a reference:
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7444902
There can be no general method. RSSI is inherently signal-specific, and hence, for each signal type, you will need a different estimator. An estimator that estimates the received signal strength of FM broadcasts will only see noise in a DVB-T signal at incredibly high noise power with no stable signal at all, whereas a DVB-T RSSI indicator would only see a slowly moving interfere in an FM signal.
I see you're using the indoor-positioning-system tag. That is a very bad thing: In an indoor scenario, fading is extremely important, and your received signal strength allow absolutely no conclusions on the distance to the transmitter. This is pretty much the definition of the indoor channel, where lots and lots of reflections overlap and interefere, and there's not always a direct line of sight between transmitter and receiver.
I'm afraid you still have quite some theory to read up on.
Related
I am wondering if it makes sense to fuse multiple GPS signals to improve my estimated result. This works fine for example for accelartion sensors, but this sensors have a white gaussian noise.
GPS sensors being mounted on the same board probably suffer from the same errors like drift or multi-path effects, which cannot be corrected by only fuse the sensor readings of this sensors. I imagine that like a constant offset in the same direction, which won t be correct just stays nearly the same.
Furthermore, I have diffrent sensor which I can mount on my drone, even RKT sensor. In my opinion, it makes no sense to fuse a d-GPS with readings from an RKT GPS.
Please correct my if I am wrong.
Thank you in advance and I hope this forum is the right spot to ask that question.
yes you can. Use EKF based approach with onboard multi GPS and multi IMU
The DJi is doing it, But it is can only prevent one of sensor failure, not the systematic drift patter. To avoid that, you need some more source such as visual odometry or lidar odometry to fuse in the EKF. GPS sate count is good meaure of how bad the position is. It ranges from 0 to 15. So when every one is 15, trust GPS more less variance. When everyone is lower than 6 add very high variance to GPS source.
Yes RTK might be better when you have direct line of sight. But once out of sight, then other GPS might be better. So totaly depends on your use case
I was wondering if I could get a cheap GPS tracking device such as this one on amazon and reprogram it to send the co-ordinates to my own server? I would then like to generate reports from the DB on my server based on dates etc. I would like to build this for a very small-scale courier company I am planning on starting.
I am an amateur/hobbyist programmer and am looking for a few pointers to help me get on the right track. Pun totally intended.
This is a very broad question. But since no one answered so far, I will just throw in my two cents. First of all, you need to know what GPS signal the (cheap) receiver can track. If it can track only single frequency at L1, there's not much you can do. You have to live with large ionosphere fluctuation error signal.
http://www.navipedia.net/index.php/Ionospheric_Delay
If it can only track code signal (not carrier phase signal) you cannot do code smoothing to reduced the noise level of code signal received.
In other words, if a GPS receiver hardware is limited, there's not much room for improvement.
Hi Im using the following RF module
http://www.apogeekits.com/rf_receiver_module_rx433.htm
on an embedded board with the PIC16F628A. Sadly, I realized that the signal strength was in analog form and couldn't get any ideas to get the RSSI reading off the pin because well my PIC is digital DUH!.
My basic idea was
To get the RSSI value from my Receiver
Send it to the PIC
Link the PIC to a PC via RS232
Plot a graph of time vs RSSI of the receiver (so I can make out how close my TX is to my RX)
I thought it was bloody brilliant at first but ive hit a dead end here. Any ideas on getting the RSSI data to my PC from this receiver would be nice.
Thanks in Advance
You can get a PIC that has an integrated ADC for sampling the analog signal. Or, you can use an external ADC chip to do the conversion. You would connect that to your PIC using SPI or I2C.
The simplest thing to do is obviously to use a more appropriate microcontroller - one with an ADC! There are many (most), including PICs (though that wouldn't be my first choice).
Attaching an external SPI or I2C ADC might be a bit tedious since having no SPI or I2C on your part, you'd have to bit-bash it. If you do that, use an SPI part - its simpler. Your sample rate will suffer and may end-up being a bit jittery if you are not careful.
Another solution is to use a voltage controlled PWM, then use the timer input capture to time the pulse width. That will give you good regularity and potentially good resolution. You can get a chip (example) to do that, or grow your own. That last option requires a triangle wave input as well as the measured (control) voltage, but on the same site...
In a similar vein, you could use a low frequency VCO (example) and use the output to clock one of the timers, then using a second timer periodically sampling the first and reset it. The count will relate to the voltage, though not necessarily a linear relationship, linearisation could be none on the PIC or at the receiving PC - I'd go for the latter - your micro will suck at arithmetic (performance wise) - even integer arithmetic, especially if it involves division.
i want to detect heart rate using iphone sdk does someone knows any method for calculating heartbeat rate?
Fast Fourier Transform is a class of algorithms that can quickly turn samples into an analysis that tells you how prominently ceratin frequencies occur in that sample. For more check out:
Wikipedia: FFT
Literate program example: Cooley-Tukey FFT
This is relevant to your problem because: (1) heart rate is itself a frequency, and (2) most of the sound that comes through the body that you can measure will be within a certain frequency range. Dropping frequencies outside this range means dropping all or mostly noise.
Good luck!
Well I've seen various implementations. Some of them use the accelerometer to detect minute movements in your arm/hand when you hold the phone, some of them can use the microphone, you could also do a manual 'tap' interface where you tap the screen while checking your own pulse.
I have an embedded device (Technologic TS-7800) that advertises real-time capabilities, but says nothing about 'hard' or 'soft'. While I wait for a response from the manufacturer, I figured it wouldn't hurt to test the system myself.
What are some established procedures to determine the 'hardness' of a particular device with respect to real time/deterministic behavior (latency and jitter)?
Being at college, I have access to some pretty neat hardware (good oscilloscopes and signal generators), so I don't think I'll run into any issues in terms of testing equipment, just expertise.
With that kind of equipment, it ought to be fairly easy to sync the o-scope to a steady clock, produce a spike each time the real-time system produces an output, an see how much that spike varies from center. The less the variation, the greater the hardness.
To clarify Bob's answer maybe:
Use the signal generator to generate a pulse at some varying frequency.
Random distribution across some range would be best.
use the signal generator (trigger signal) to start the scope.
the RTOS has to respond, do it thing and send an output pulse.
feed the RTOS output into input 2 of the scope.
get the scope to persist/collect mode.
get the scope to start on A , stop on B. if you can.
in an ideal workd, get it to measure the distribution for you. A LeCroy would.
Start with a much slower trace than you would expect. You need to be able to see slow outliers.
You'll be able to see the distribution.
Assuming a normal distribution the SD of the response time variation is the SOFTNESS.
(This won't really happen in practice, but if you don't get outliers it is reasonably useful. )
If there are outliers of large latency, then the RTOS is NOT very hard. Does not meet deadlines well. Unsuitable then it is for hard real time work.
Many RTOS-like things have a good left edge to the curve, sloping down like a 1/f curve.
Thats indicitive of combined jitters. The thing to look out for is spikes of slow response on the right end of the scope. Keep repeating the experiment with faster traces if there are no outliers to get a good image of the slope. Should be good for some speculative conclusion in your paper.
If for your application, say a delta of 1uS is okay, and you measure 0.5us, it's all cool.
Anyway, you can publish the results ( and probably in the publish sense, but certainly on the web.)
Link from this Question to the paper when you've written it.
Hard real-time has more to do with how your software works than the hardware on its own. When asking if something is hard real-time it must be applied to the complete system (Hardware, RTOS and application). This means hard or soft real-time is system design issues.
Under loading exceeding the specification even a hard real-time system will fail (hopefully with proper failure indication) while a soft real-time system with low loading would give hard real-time results. How much processing must happen in time and how much pre/post processing can be performed is the real key to hard/soft real-time.
In some real-time applications some data loss is not a failure it should just be below a certain level, again a system criteria.
You can generate inputs to the board and have a small application count them and check at what level data is going to be lost. But that gives you a rating specific to that system running that application. As soon as you start doing more processing your computational load increases and you now have a different hard real-time limit.
This board will running a bare bones scheduler will give great predictable hard real-time performance for most tasks.
Running a full RTOS with heavy computational load you probably only get soft real-time.
Edit after comment
The most efficient and easiest way I have used to measure my software's performance (assuming you use a schedular) is by using a free running hardware timer on the board and to time stamp my start and end of my cycle. Or if you run a full RTOS time stamp you acquisition and transition. Save your Max time and run a average on the values over a second. If your average is around 50% and you max is within 20% of your average you are OK. If not it is time to refactor your application. As your application grows the cycle time will grow. You can monitor the effect of all your software changes on your cycle time.
Another way is to use a hardware timer generate a cyclical interrupt. If you are in time reset the interrupt. If you miss the deadline you have interrupt handler signal a failure. This however will only give you a warning once your application is taking to long but it rely on hardware and interrupts so you can't miss.
These solutions also eliminate the requirement to hook up a scope to monitor the output since the time information can be displayed in any kind of terminal by a background task. If it is easy to monitor you will monitor it regularly avoiding solving the timing problems at the end but as soon as they are introduced.
Hope this helps
I have the same board here at work. It's a slightly-modified 2.6 Kernel, I believe... not the real-time version.
I don't know that I've read anything in the docs yet that indicates that it is meant for strict RTOS work.
I think that this is not a hard real-time device, since it runs no RTOS.
I understand being geek, but using oscilloscope to test a computer with ethernet/usb/other digital ports and HUGE internal state (RAM) is both ineffective and unreliable.
Instead of watching wave forms, you can connect any PC to the output port and run proper statistical analysis.
The established procedure (if the input signal is analog by nature) is to test system against several characteristic inputs - traditionally spikes, step functions and sine waves of different frequencies - and measure phase shift and variance for each input type. Worst case is then used in specifications of the system.
Again, if you are using standard ports, you can easily generate those on PC. If the input is truly analog, a separate DAC or simply a good sound card would be needed.
Now, that won't say anything about OS being real-time - it could be running vanilla Linux or even Win CE and still produce good and stable results in those tests if hardware is fast enough.
So, you need to simulate heavy and varying loads on processor, memory and all ports, let it heat and eat memory for a few hours, and then repeat tests. If latency stays constant, it's hard real-time. If it doesn't, under any load and input signal type, increase above acceptable limit, it's soft. Otherwise, it's advertisement.
P.S.: Implication is that even for critical systems you don't actually need hard real-time if you have hardware.